class_docstr: This layer performs an elementwise merge of its input layers.
  It requires all input layers to have the same output shape.
  
  Parameters
  ----------
  incomings : a list of :class:`Layer` instances or tuples
      the layers feeding into this layer, or expected input shapes,
      with all incoming shapes being equal
  
  merge_function : callable
      the merge function to use. Should take two arguments and return the
      updated value. Some possible merge functions are ``theano.tensor``:
      ``mul``, ``add``, ``maximum`` and ``minimum``.
  
  cropping : None or [crop]
      Cropping for each input axis. Cropping is described in the docstring
      for :func:`autocrop`
  
  See Also
  --------
  ElemwiseSumLayer : Shortcut for sum layer.
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code: def __init__(
      self, incomings, merge_function, cropping=None, **kwargs
  ):
      super(ElemwiseMergeLayer, self).__init__(incomings, **kwargs)
      self.merge_function = merge_function
      self.cropping = cropping
  
file_path: Lasagne/lasagne/layers/merge.py
imports: import theano.tensor
  from .base import MergeLayer
label_desc: Use image node_id 1 to create a new ElemwiseMergeLayer object from inherited base classes: MergeLayer with example: obj = ElemwiseMergeLayer(incomings, merge_function, cropping)